is personal choice > predictive analytics?

Let's start with my truth, I think I know the answer to the question but am not sure because I am not a predictive analytics expert. In fact, I'm far from it and am likely behind the AI times because I retain a high degree of confidence in the choices I make, how and when I make them. I like to make decisions for myself and continue to do so. It's a process I enjoy.

As I understand and could be wrong, based on decisions and choices I make online, predictive analytics are able to 'know' either what I will likely do or what I should do at any moment in time. Systems can tell me what I need to do when I need to do it. For instance, I attend a Bible Study every Tuesday morning and when I am finished I go to my favorite coffee shop to drink coffee and attend one to one meetings with executives scheduled for the morning. I love my Tuesday mornings as serendipitously I run into old friends or newer acquaintances at the coffee shop every week. Not long ago SIRI suggested via text I go to my favorite coffee shop Tuesday morning as I was headed that way.

I didn't ask to be alerted. I knew where I was going and why. Did I need SIRI to suggest where I go without being asked?

I'm sure that soon SIRI will ask me if I want her to order my coffee with almond milk so it's ready as I walk in and that would be nice but is it necessary? Last week I walked into the coffee shop at 8:45 as I do just about every week and was greeted with a "Hi Mr. Stringer. here's your coffee with Almond milk." I was pleased, the hostess was pleased I was pleased and as I think we all would agree there's something really nice about the human touch.

Has M. Gladwell written on this yet?

This week I have been inundated with advertisements for Executive Career sites with 100m candidates in their database with predictive analytics provided on each candidate helping to determine the best time for a recruiter to call with the best position and size company according to the candidate's previous online actions and statements. Interesting and appears to be of value but I question the value.

And here's why?

I am not the greatest recruiter but I have been recruiting executives for 40 years. I am not the greatest recruiting technologist but I started building the recruitment technology Hire.com in 1994 and with the help of others successfully brought our enterprise SaaS solution to the market in 1997. Interestingly, some of the changes I expected to see in the recruitment technology marketplace over the past 20 years have not occurred, maybe because I based my expectations on common sense instead of technology.

My common sense then and today.

I believe people know up to 3 industries, titles, company sizes, and locations of interest for career transition and believe the companies seeking talent know the industries, titles, companies and company locations (BTW: virtual is a location in my book) they would like to recruit talent from for the role they need to fill. Could the foundation of successful career transition matching be this simple? Do we need predictive analytics to decipher who and when OR might we rely on people sharing, either publicly or anonymously the open positions they want to see and consider?

Can we state the career opportunity want because we know, or should we rely on a system to predict the positions we would like to see and consider?

I for one believe the power of the Internet truly lies in the ability for people to own and choose where and how their information is used. It appears that personal 'opt-in' never successfully made it into the Internet business models of today, and may have been a facade so the technology could accomplish what they have today, the ability to know and predict what we need and when. As we know, our information is sold, it has value but without our input.

As I started, I don't know the answer but feel strongly that the repetition of making personal choices ourselves and the consequences we hold ourselves accountable for, good or bad are a good thing.

We call it, learning from experience.